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GHSA-67wx-r9xr-x75x
No affected components available
Summary
User provided image and backup tarballs would be unpacked and YAML files parsed without any size restrictions. This was making it easy for an authenticated user to provide a crafted image or backup tarball that when parsed by Incus would lead to a very large YAML document being loaded into memory, potentially causing the entire server to run out of memory.
Details
It was found that getImageMetadata and backup.GetInfo call yaml.NewDecoder(tr).Decode() directly on the tar reader without limiting how many bytes the YAML decoder can consume. The tar entry hdr.Size is not checked before decoding.
A tar archive can be crafted in which metadata.yaml or backup/index.yaml declares a large size in the tar header, causing the YAML decoder to read and allocate proportional memory on the server. The gopkg.in/yaml.v2 library mitigates YAML alias and anchor bombs, such as “billion laughs,” through its built-in excessive-aliasing check. However, large flat YAML documents with many keys or long string values can still produce linear but amplified memory consumption of approximately 5x to 6x the input size.
A 200 MB tar entry for metadata.yaml may cause approximately 1.2 GB of heap allocations during decode, which may be sufficient to trigger an out-of-memory condition on a constrained daemon or significantly degrade service. Because the decode occurs in the daemon process, excessive garbage-collection pressure can affect concurrent operations. Appropriate API permissions are required to upload an image or backup archive.
Mitigating factors include the fact that the amplification is linear rather than exponential, at approximately 5x to 6x, and that upload bandwidth is the practical bottleneck for delivering large payloads.
Affected Files:
- https://github.com/lxc/incus/blob/v6.22.0/cmd/incusd/images.go#L1456
- https://github.com/lxc/incus/blob/v6.22.0/internal/server/backup/backup_info.go#L87
- https://github.com/lxc/incus/blob/v6.22.0/internal/server/backup/backup_info.go#L115
Image metadata parsing reads YAML directly from the tar stream: Affected Code:
if hdr.Name == "metadata.yaml" || hdr.Name == "./metadata.yaml" {
err = yaml.NewDecoder(tr).Decode(&result)
Backup info parsing does the same:
Affected Code:
if hdr.Name == backupIndexPath {
err = yaml.NewDecoder(tr).Decode(&result)
if result.Config == nil && hdr.Name == "backup/container/backup.yaml" {
err = yaml.NewDecoder(tr).Decode(&result.Config)
This was confirmed as follows:
Command:
go test ./test/fuzz -run='TestUnboundedYAMLMetadataDecode' -count=1 -v
Output:
=== RUN TestUnboundedYAMLMetadataDecode
image_metadata_poc_test.go:80: metadata.yaml size: 10.2 MB
image_metadata_poc_test.go:113: metadata.yaml hdr.Size = 10688940 bytes (10.2 MB) -- no size
check exists in getImageMetadata before yaml.NewDecoder(tr).Decode()
image_metadata_poc_test.go:124: decoded 50000 properties from 10.2 MB metadata.yaml
image_metadata_poc_test.go:125: yaml.NewDecoder(tr).Decode() accepted 10.2 MB metadata.yaml
with 50000 properties -- no hdr.Size check or io.LimitReader in images.go:1457 or
backup_info.go:88
--- FAIL: TestUnboundedYAMLMetadataDecode (0.11s)
FAIL
It is recommended to add a size check on hdr.Size before YAML decoding and to wrap the tar reader in io.LimitReader.
Proposed Fix:
const maxMetadataSize = 1 << 20 // 1 MB
if hdr.Size > maxMetadataSize {
return nil, fmt.Errorf("metadata entry too large: %d bytes", hdr.Size)
}
err = yaml.NewDecoder(io.LimitReader(tr, maxMetadataSize)).Decode(&result)
A patch is available at https://github.com/lxc/incus/releases/tag/v7.0.0.
Credit
This issue was discovered and reported by the team at 7asecurity (https://7asecurity.com/)
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability. The vulnerability can affect other systems as well, not just the initial system. There is a low impact on the availability of the system.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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